handle nans properly

Author: Tyler Hutcherson

main.py

@@ -48,11 +48,19 @@
 print("Validating a single record:", flush=True)
 print(gtrends_json['data'][0], flush=True)
 
-# Convert to pandas df and handles string NaN's coming through data engine
+# Convert to pandas df
 gtrends = pd.DataFrame.from_records(gtrends_json['data'])\
-    .pivot(index='date', values='interest', columns='keyword')\
-    .replace({'NaN': None})\
-    .fillna(method='pad')
+    .pivot(index='date', values='interest', columns='keyword')
+
+# Deal with potential nans
+for col in gtrends.columns:
+    if 'NaN' in gtrends[col].values:
+        gtrends[col].replace({'NaN': None}, inplace=True)
+    else:
+        continue
+
+# If there are nans, fill using pad method
+gtrends.fillna(method='pad', inplace=True)
 
 # Set proper date format
 gtrends.index = pd.to_datetime(gtrends.index)